Using wavelet decomposition to support progressive and approximate range-sum queries over data cubes
Yi-Leh Wu, Divyakant Agrawal, Amr El Abbadi · 2000
Data cubes are designed to pro vide aggregate information that can be used to analyze the contents of databases and data w arehouses.A range query applies an aggregation operation (e.g., SUM, A VERAGE) over all selected cells in a data cube, where the selection is speci ed by providing ranges of values on dierent dimensions.Previous approaches to process the range sum query on data cubes (e.g., pre x sum) have l o w query costs but have high update costs.We use the discrete wavelet transformation to decompose a data cube into w avelet coecien ts of dierent resolutions.The resulting decomposed data cube can be used for progressiv eand appro ximatequery processing.This new approach can handle clustered and sparse data gracefully and can provide ecient performance for both queries and updates, which m a k es the wavelet decomposition technique suitable for dynamic data cube environments.